Recovering physical parameters from galaxy spectra using MOPED

Monthly Notices of The Royal Astronomical Society, 2005

The study of stellar populations in galaxies is entering a new era with the availability of large and high-quality data bases of both observed galactic spectra and state-of-the-art evolutionary synthesis models. In this paper we investigate the power of spectral synthesis as a means to estimate the physical properties of galaxies. Spectral synthesis is nothing more than the decomposition of an observed spectrum in terms of a superposition of a base of simple stellar populations of various ages and metallicities, producing as output the star formation and chemical histories of a galaxy, its extinction and velocity dispersion. Our implementation of this method uses the recent models of Bruzual & Charlot and observed spectra in the 3650–8000 Å range. The reliability of this approach is studied by three different means: (1) simulations, (2) comparison with previous work based on a different technique, and (3) analysis of the consistency of results obtained for a sample of galaxies from the Sloan Digital Sky Survey (SDSS).We find that spectral synthesis provides reliable physical parameters as long as one does not attempt a very detailed description of the star formation and chemical histories. Robust and physically interesting parameters are obtained by combining the (individually uncertain) strengths of each simple stellar population in the base. In particular, we show that, besides providing excellent fits to observed galaxy spectra, this method is able to recover useful information on the distributions of stellar ages and, more importantly, stellar metallicities. Stellar masses, velocity dispersion and extinction are also found to be accurately retrieved for realistic signal-to-noise ratios.We apply this synthesis method to a volume-limited sample of 50 362 galaxies from the SDSS Data Release 2, producing a catalogue of stellar population properties. Emission lines are also studied, their measurement being performed after subtracting the computed starlight spectrum from the observed one. A comparison with recent estimates of both observed and physical properties of these galaxies obtained by other groups shows good qualitative and quantitative agreement, despite substantial differences in the methods of analysis. The confidence in the present method is further strengthened by several empirical and astrophysically reasonable correlations between synthesis results and independent quantities. For instance, we report the existence of strong correlations between stellar and nebular metallicities, stellar and nebular extinctions, mean stellar age and equivalent width of Hα and 4000-Å break, and between stellar mass and velocity dispersion.

Cornell University - arXiv, 2014

We examine the star formation histories (SFHs) of galaxies in smoothed particle hydrodynamics (SPH) simulations, compare them to parametric models that are commonly used in fitting observed galaxy spectral energy distributions, and examine the efficacy of these parametric models as practical tools for recovering the physical parameters of galaxies. The commonly used τ-model, withṀ * ∝ e −(t−ti)/τ , provides a poor match to the SFH of our SPH galaxies, with a mismatch between early and late star formation that leads to systematic errors in predicting colours and stellar mass-to-light ratios. A one-parameter lin-exp model, withṀ * ∝ t e −(t−ti)/τ , is much more successful on average, but it fails to match the late-time behaviour of the bluest, most actively starforming galaxies and the passive, "red and dead" galaxies. We introduce a 4-parameter model, which transitions from lin-exp to a linear ramp after a transition time t tr , which describes our simulated galaxies very well. In practice, we can fix two parameters (t i and t tr) without significant loss of accuracy. We test the ability of these parametrised models to recover (at z = 0, 0.5, and 1) the stellar mass-to-light ratios, specific star formation rates, and stellar population ages from the galaxy colours, computed from the full SPH star formation histories using the FSPS code of Conroy et al. (2009). Fits with τ-models systematically overestimate M * /L by ∼ 0.2 dex, overestimate population ages by ∼ 1 − 2 Gyr, and underestimateṀ * /M * by ∼ 0.05 dex. Fits with lin-exp are less biased on average, but the 4-parameter model yields the best results for the full range of galaxies. Marginalizing over the free parameters of the 4-parameter model leads to slightly larger statistical errors than 1-parameter fits but essentially removes all systematic biases, so this is our recommended procedure for fitting real galaxies.

2007

We present a methodological study to find out how far back and to what precision star formation histories of galaxies can be reconstructed from CMDs, from integrated spectra and Lick indices, and from integrated multi-band photometry. Our evolutionary synthesis models GALEV allow to describe the evolution of galaxies in terms of all three approaches and we have assumed typical observational uncertainties for each of them and then investigated to what extent and accuracy different star formation histories can be discriminated. For a field in the LMC bar region with both a deep CMD from HST observations and a trailing slit spectrum across exactly the same field of view we could test our modelling results against real data.

Publications of The Astronomical Society of The Pacific, 1996

ABSTRACT. This paper represents a collective effort to provide an extensive electronic data base useful for the interpretation of the spectra and evolution of galaxies. A broad variety of empirical and theoretical data is discussed here, and the data are made fully available in the AAS CD-ROM Series, Vol. 7. Several empirical stellar libraries are part of this data base. They cover the ultraviolet spectral range observed with WE, optical data from different ground-based telescopes, and ground-based infrared data. Spectral type coverage depends on the wavelength, but is mostly complete for types O to M and luminosity classes V to I. A large metallicity range is covered as well. Theoretical libraries of selected spectral indices of cool stars and of stellar continuum fluxes in the temperature range 2000-50,000 Κ as well as Wolf-Rayet energy distributions are presented. Several libraries of star clusters and early-type galaxies have been selected for this data base. We discuss an extensive set of empirical spectral templates covering the wavelength region from 1200 to 9800 Â, as well as narrow-band line indices in a large number of passbands. Bench-mark spectra of nearby galaxies for model tests are included as well. We compiled numerous evolutionary models and isochrones for stars of all mass ranges of interest, wide metallicity range, and for all evolutionary phases, including the pre-main-sequence phase. The majority of the models have been computed by the Geneva and Padova groups. Evolutionary synthesis models computed by several independent groups are made available. They can be applied to old and young systems, and are optimized with respect to different aspects of input physics. The model predictions include stellar (colors, magnitudes, absorption features) and nebular (emission-line fluxes) properties. Finally, we present models of ionized gas to be used for the interpretation of active galactic nuclei and young star-forming galaxies. The community is encouraged to make use of this electronic data base and to perform a critical comparison between the individual datasets.

Monthly Notices of the …, 2006

Astronomical Journal, 2005

An empirical method of modeling the stellar spectrum of galaxies is proposed, based on two successive applications of Principal Component Analysis (PCA). PCA is first applied to the newly available stellar library STELIB, supplemented by the J, H and K$_{s}$ magnitudes taken mainly from the 2 Micron All Sky Survey (2MASS). Next the resultant eigen-spectra are used to fit the observed spectra of a sample of 1016 galaxies selected from the Sloan Digital Sky Survey Data Release One (SDSS DR1). PCA is again applied, to the fitted spectra to construct the eigen-spectra of galaxies with zero velocity dispersion. The first 9 galactic eigen-spectra so obtained are then used to model the stellar spectrum of the galaxies in SDSS DR1, and synchronously to estimate the stellar velocity dispersion, the spectral type, the near-infrared SED, and the average reddening. Extensive tests show that the spectra of different type galaxies can be modeled quite accurately using these eigen-spectra. The method can yield stellar velocity dispersion with accuracies better than 10%, for the spectra of typical S/N ratios in SDSS DR1.

Monthly Notices of The Royal Astronomical Society, 2000

We present a method for radical linear compression of datasets where the data are dependent on some number $M$ of parameters. We show that, if the noise in the data is independent of the parameters, we can form $M$ linear combinations of the data which contain as much information about all the parameters as the entire dataset, in the sense that the Fisher information matrices are identical; i.e. the method is lossless. We explore how these compressed numbers fare when the noise is dependent on the parameters, and show that the method, although not precisely lossless, increases errors by a very modest factor. The method is general, but we illustrate it with a problem for which it is well-suited: galaxy spectra, whose data typically consist of $\sim 10^3$ fluxes, and whose properties are set by a handful of parameters such as age, brightness and a parametrised star formation history. The spectra are reduced to a small number of data, which are connected to the physical processes entering the problem. This data compression offers the possibility of a large increase in the speed of determining physical parameters. This is an important consideration as datasets of galaxy spectra reach $10^6$ in size, and the complexity of model spectra increases. In addition to this practical advantage, the compressed data may offer a classification scheme for galaxy spectra which is based rather directly on physical processes.

The Astrophysical Journal, 2021

We develop a data-driven model to map stellar parameters (T eff , log g, and [Fe/H]) accurately and precisely to broad-band stellar photometry. This model must, and does, simultaneously constrain the passband-specific dust reddening vector in the Milky Way, R. The model uses a neural network to learn the (de-reddened) absolute magnitude in one band and colors across many bands, given stellar parameters from spectroscopic surveys and parallax constraints from Gaia. To demonstrate the effectiveness of this approach, we train our model on a dataset with spectroscopic labels from LAMOST, APOGEE and GALAH, Gaia parallaxes, and optical and near-infrared photometry from Gaia, Pan-STARRS 1, 2MASS and WISE. Testing the model on these datasets leads to an excellent fit and a precise-and by construction accurate-prediction of the color-magnitude diagrams in many bands. This flexible approach rigorously links spectroscopic and photometric surveys, and also results in an improved, T eff-dependent R. As such, it provides a simple and accurate method for predicting photometry in stellar evolutionary models. Our model will form a basis to infer stellar properties, distances and dust extinction from photometric data, which should be of great use in 3D mapping of the Milky Way. Our trained model may be obtained at

Arxiv preprint astro-ph/ …, 2004

The study of stellar populations in galaxies is entering a new era with the availability of large and high quality databases of both observed galactic spectra and state-of-theart evolutionary synthesis models. In this paper we investigate the power of spectral synthesis as a mean to estimate physical properties of galaxies. Spectral synthesis is nothing more than the decomposition of an observed spectrum in terms of a superposition of a base of simple stellar populations of various ages and metallicities, producing as output the star-formation and chemical histories of a galaxy, its extinction and velocity dispersion. Our implementation of this method uses the Bruzual & Charlot (2003) models and observed spectra in the 3650-8000Å range. The reliability of this approach is studied by three different means: (1) simulations, (2) comparison with previous work based on a different technique, and (3) analysis of the consistency of results obtained for a sample of galaxies from the Sloan Digital Sky Survey (SDSS).

2009

Retrieving the Star Formation History (SFH) of a galaxy out of its integrated spectrum is the central goal of stellar population synthesis. Recent advances in evolutionary synthesis models have given new breath to this old field of research. Modern spectral synthesis techniques incorporating these advances now allow the fitting of galaxy spectra on an Å-by-Å. These detailed fits are useful for a number of studies, like emission line, stellar kinematics, and specially galaxy evolution. Applications of this semi-empirical approach to mega data sets are teaching us a lot about the lives of galaxies. The STARLIGHT spectral synthesis code is one of the tools which allows one to harness this favorable combination of plentifulness of data and models. To illustrate this, we show how SFHs vary across classical emission line diagnostic diagrams. Systematic trends are present along both the star-forming and active-galaxy sequences. We also briefly describe experiments with new versions of evol...